Understanding local HIV sub-epidemics is key to eliminating the HIV epidemic. Real-time phylodynamics is critical, as only real-time monitoring of HIV transmission dynamics and identification of emerging HIV sub- epidemics could guide real-time public policy decisions. Results of this study will prove the feasibility of real- time monitoring of HIV transmission clusters in limited-resource settings. We hypothesize that newly diagnosed individuals with detectable HIV RNA are disproportionately linked to active HIV sub-epidemics, i.e. clusters with effective reproductive number Re > 1.0. We will perform HIV genotyping in real time using novel nanopore MinION technology. This will allow us to assess phylogenetic linkages between individuals with detectable HIV RNA and active HIV sub-epidemics in real time. A model for real-time monitoring of HIV cluster dynamics will be the study outcome. Specific Aim 1. Real-time HIV genotyping: Feasibility of real-time HIV genotyping in the field, and results validation. We will enroll 750 participants?newly diagnosed individuals and people initiating ART? through referrals. We will perform point-of-care testing of viral load, test the feasibility of real-time HIV genotyping in the field, perform long-range HIV amplification, barcoding, and sequencing using novel nanopore MinION technology in the field, and generate 667 (up to 750) near full-length HIV genomes using nanopore technology in the field in real time. To validate results, we will compare data obtained using nanopore MinION in the field and next-generation sequencing data generated by Illumina HiSeq. Specific Aim 2. Real-time phylogenetic cluster analysis: Feasibility of monitoring HIV transmission clusters and active HIV sub-epidemics in real time. To assess HIV cluster dynamics in real time, we will infer phylogenies of newly generated HIV sequences (n=667; up to 750). We will enumerate HIV transmission clusters by identifying phylogenetically distinct HIV sub-epidemics. We will reconstruct dated phylogenies and identify active HIV sub-epidemics?i.e., those with an effective reproduction number Re ? 1.0. We will estimate linkages between newly diagnosed individuals with detectable viral load and active HIV sub-epidemics. We will perform HIV drug-resistance analysis and return the results to clinicians and participants in real time. The proposed study has the potential to develop a model for real-time monitoring of HIV transmission clusters, and for identifying emerging HIV sub-epidemics in real time. The study will demonstrate that real-time monitoring of HIV transmission clusters is feasible, will validate the results, and will determine whether real- time drug-resistance testing is realistic and could be performed in the field. We will test whether the cost of real-time HIV genotyping in the field could be dropped to $34 per sample.